The goal of this experiment was to determine what if any effect two different types of warnings have the brake reaction time of distracted commercial motor vehicle operators. The warning conditions were: No Warning, Auditory Tire Skid Warning, and One Second Brake Pulse Warning. Each participant was distracted via a distracter task during the experiment. As the participants were distracted, an obstacle was launched out into their forward path. Each participant received his/her appropriate warning, according to what condition they were placed, when the obstacle entered their headway. It was determined that the Auditory Tire Skid Warning aided in decreasing the movement times, while the One Second Brake Pulse Warning aided in decreasing the number of collisions with the barrels and speed at contact with the barrels. / Master of Science

This thesis presents collision avoidance integrated with lane keeping and adaptive cruise control for a car. Collision avoidance is the ability to avoid obstacles that are in the vehicle's path, without causing damage to the obstacle or car. There are three types of collision avoidance controllers, passive, active, and semi-active. This thesis is designed using active collision avoidance controllers. There are two controllers developed for collision avoidance in this paper. They are an optimal controller and a fuzzy controller. The optimal vehicle trajectory, which maximizes the distance to an obstacle and changes lanes, is derived. The optimal collision avoidance controller is a closed loop controller; with the decisions based on the current state. The fuzzy controller makes decisions based on the system rules. A simulation environment was created to compare these two controllers as viable solutions for collision avoidance. The environment uses MATLAB/Simulink for simulation of the vehicle as well as the optimal and fuzzy controllers. The simulation incorporates system blocks of the kinematics of a car, navigation, states, control law, and velocity controller. Once the controllers are fully developed and tested in the simulation environment, they are implemented and tested on the platform vehicle. This verifies the real world performance of the controllers. The platform vehicle is a modified radio controlled car. This car is completely autonomous. The car has onboard sensors that allow it to follow a white piece of tape as well as detect obstacles. / Master of Science

Presented in this thesis is a collision avoidance algorithm designed around an arc path model. The algorithm was designed for use on Virginia Tech robots entered in the 2003 and 2004 Intelligent Ground Vehicle Competition (IGVC) and on our 2004 entry into the DARPA Grand Challenge. The arc path model was used because of the simplicity of the calculations and because it can accurately represent the base kinematics for Ackerman or differentially steered vehicles. Clothoid curves have been used in the past to create smooth paths with continuously varying curvature, but clothoids are computationally intensive. The circular arc algorithm proposed here is designed with simplicity and versatility in mind. It is readily adaptable to ground vehicles of any size and shape. The algorithm is also designed to run with minimal tuning. The algorithm can be used as a stand alone reactive collision avoidance algorithm in simple scenarios, but it can be better optimized for speed and safety when guided by a global path planner. A complete navigation architecture is presented as an example of how obstacle avoidance can be incorporated in the algorithm. / Master of Science

The autonomous operation of Uncrewed Aircraft Systems (UAS) beyond the pilot in command's visual line of sight is currently restricted due to a lack of cost-effective surveillance sensors robust enough to operate in low-level airspace. The current sensors available either have have high accuracy of locating targets but are too short of a range to be usable or have long ranges but have gaps in coverage due to varying terrain. Sensor fusion is one possible method of combining the strengths of different sensors to increase the overall airspace surveillance quality to allow for robust detect and avoid (DAA) capabilities; enabling beyond visual line of sight operations. This thesis explores some of the current techniques and challenges to use sensor fusion for collision avoidance between crewed aircraft and UAS. It demonstrates an example method of sensor fusion using data from two radars and an ADS-B receiver. In this thesis, a test bed for ground-based airspace monitoring surveillance is proposed for a low cost method of long-term sensor evaluation. Lastly, an potential method of a heterogeneous, score-based, sensor fusion is presented and simulated. / Master of Science / Long range operations of Uncrewed Aircraft Systems (UAS) are currently restricted due to a lack of cost-effective surveillance sensors that work well enough near the ground in the presence changing terrain. The current sensors available either have have high accuracy of locating targets but are too short of a range to be usable or have long ranges but have gaps in coverage due to varying terrain. Sensor fusion is a solution to this problem by combining the strengths of different sensors to allow for better collision avoidance capabilities; enabling these long range operations. This thesis explores some of the current techniques and challenges to use sensor fusion for collision avoidance between crewed aircraft and UAS. It demonstrates an example method of sensor fusion using data from two radars and an ADS-B receiver. In this thesis, a test bed for ground-based airspace monitoring surveillance is proposed for long-term sensor testing. Lastly, an potential method of a sensor fusion using different types of sensors is presented and simulated.

Highly Automated Vehicles (AVs) have the capability to revolutionize the transportation system. These systems have the possibility to make roads safer as AVs do not have limitations that human drivers do, many of which are common causes of vehicle crashes (e.g., distraction or fatigue) often defined generically as human error. The deployment of AVs is likely to be very gradual however, and there will exist situations in which the AV will be driving in close proximity with human drivers across the foreseeable future. Given the persistent crash problem in which the makority of crashes are attributed to driver error, humans will continue to create potential collision scenarios that an AV will be expected to try and avoid or mitigate if developed appropriately. The absence of unreasonable risk in an AVs ability to comprehend and react in these situations is referred to as operational safety. Unlike advanced driver assistance systems (ADAS), highly automated vehicles are required to perform the entirety of the dynamic driving task (DDT) and have a greater responsibility to achieve a high level of operational safety. To address this concern, scenario-based testing has increasingly become a popular option for evaluating AV performance. On a functional level, an AV typically consists of three basic systems: the perception system, the decision and path planning system, and vehicle motion control system. A minimum level of performance is needed in each of these functional blocks to achieve an adequate level of operational safety. The goal of this study was to investigate the effects that perception system performance (i.e., target object state errors) has on vehicle operational safety in collision scenarios similar to that created by human drivers. In the first part of this study, recent annual crash data was used to define a relevant crash population of possible scenarios involving intersections that an AV operating as an urban taxi may encounter. Common crash maneuvers and characteristics were combined to create a set of testing scenarios that represent a high iii percentage of the overall crash population. In the second part of this study, each test scenario was executed using an AV test platform during closed road testing to determine possible real-world perception system performance. This provided a measure of the error in object detection measurements compared to the ideal (i.e., where a vehicle was detected to be compared to where it actually was). In the third part of this study, a set of vehicle simulations were performed to assess the effect of perception system performance on crash outcomes. This analysis simulated hypothetical crashes between an AV and one other collision partner. First an initial worst-case impact configuration was defined and was based on injury outcomes seen in crash data. The AV was then simulated to perform a variety of evasive maneuvers based on an adaptation of a non-impaired driver model. The impact location and orientation of the collision partner was simulated as two states: one based on the object detection of an ideal perception system and the other based on the object detection of the perception system from the AV platform used during the road testing. For simulations in which the two vehicles contacted each other, a planar momentum-impulse model was used for impact modeling and injury outcomes were predicted using an omni-directional injury model taken from recent literature. Results from this study indicate that errors in perception system measurements can change the perceived occupant injury risk within a crash. Sensitivity was found to be dependent on the specific crash type as well as what evasive maneuver is taken. Sensitivities occurred mainly due to changes in the principal direction of force for the crash and the interaction within the injury risk prediction curves. In order to achieve full operational safety, it will likely be important to understand the influence that each functional system (perception, decision, and control) may have on AV performance in these crash scenarios. / Master of Science / Highly Automated Vehicles (AVs) have the capability to revolutionize the transportation system. These systems have the possibility to make roads safer as AVs do not have many of the limitations that human drivers do, many of which are common causes of vehicle crashes (e.g., distraction or fatigue). AVs will be expected to drive alongside human drivers, and so these drivers are likely to continue to be at fault in causing crashes. As part of ensuring safety, AVs will reasonably be expected to try and avoid or help reduce the severity of these crashes. AVs operate using three main systems: the perception system which consists of sensors that see the objects around the AV, the decision and path planning system, which makes decision on what the AV will do, and the vehicle motion control system. Due to the nature of the real-world, these systems may not work exactly as intended which may affect the ability of the AV to react to possible crash scenarios. Because of this, the goal of this study was to investigate the effects that perception system performance (i.e., target object state errors) has on the ability of an AV to react to crash scenarios similar to those created by human drivers. This study first defined crash scenarios using real-world crash data. A real-world perception system was then tested in these scenarios to determine object detection performance. Based on this performance, effects on safety were assessed through vehicle crash simulations. Results from this analysis showed that safety can vary based on both perception system performance and crash scenario. This highlights that it will be important to address system performance in order to achieve high levels of driving safety.

Contention resolution coordinates access to a shared communication channel divided into synchronized slots. For any fixed slot, a packet can be sent, leading to three outcomes: empty (no packet sent), successful (one packet sent), or collision (multiple packets sent). Each slot provides ternary feedback: empty, successful, or collision. Much of the prior work has mainly focused on optimizing the makespan, the number of slots needed for all packets to succeed. However, in many modern systems, collisions also incur time costs, which existing algorithms do not address. In this thesis, we design and analyze a randomized contention-resolution algorithm, Collision-Evasion Backoff, that optimizes both the makespan and the cost of collisions. In our research, �� ≥ 2 packets are initially present in the system, and each collision has a known cost C, where 1 ≤ C ≤ ���� for a known ��. With error probability polynomially small in ��, Collision-Evasion Backoff guarantees that all packets succeed with makespan �� (��√C log(��)) and a total expected collision cost of �� (��√C log2 (��)).

Cette thèse, réalisée en partenariat avec Rockwell-Collins France, s'inscrit dans le cadre du développement d'un radar FMCW aéroporté de détection d'obstacles fonctionnant en bande X. Dans cette thèse, nous nous plaçons dans le contexte plus général de détection de cibles présentant un risque de collision avec le porteur radar dans du fouillis de sol. Les performances de détection des cibles d'intérêt diminuent grandement lorsqu'elles se retrouvent dans les zones de fouillis. Le principal objectif de cette thèse réside ainsi dans la conception de traitements en vue d'améliorer les capacités de détection et de reconnaissance de cibles présentant un risque de collision avec le porteur radar dans les zones de fouillis de sol. Dans un premier temps, nous effectuons une revue des traitements adaptés à la détection d'obstacles par un radar aéroporté FMCW: formation de faisceaux conventionnelle, compensation de migration distance, et création d'une cartographie distance-vitesse par double FFT. Dans un second temps, nous utilisons ensuite un traitement d'antennes adaptatif pour séparer en élévation le fouillis de sol et d'éventuels obstacles situés au-dessus du sol pouvant présenter un risque pour le porteur (câbles, pylônes, immeubles, ...). Dans la seconde partie de cette thèse, nous incluons une information supplémentaire sur le signal temporel d'une case distance avec un temps d'intégration plus long~: la variation de fréquence Doppler des cibles. Une cible de collision ou un câble ne changent pas de fréquence tandis qu'un élément au sol aura une variation connue dépendant de la vitesse du porteur et de son angle de vue. Cette information nous a tout d'abord permis de séparer le signal d'un pylône et d'un câble, pour ensuite séparer la cible de collision du fouillis de sol. Enfin, nous effectuons la détection adaptative d'une cible mobile de collision étendue en distance et noyée dans le fouillis de sol. Les algorithmes développés dans cette thèse ont été testés avec succès sur données expérimentales. / This thesis, in collaboration with Rockwell-Collins France, forms part of the development of an X-band FMCW airborne radar designed for obstacles detection and collision avoidance. More precisely, this thesis deals with the problem of detecting targets which exhibit a collision trajectory with the radar carrier, in presence of ground clutter. Target detection performances are highly degraded when the targets of interest fall into ground clutter. The main goal of this thesis is to develop signal processing methods to increase radar detection capacities and recognition for collision targets inside ground clutter. First, we give a brief review of signal processing methods for target detection using an airborne FMCW radar : conventional beamforming, range migration compensation, double-FFTs for Range-Doppler Map visualization. We then derive an adaptive antenna array processing to separate ground clutter and fixed hazardous obstacles above the ground (cables, pylons, buildings, ...) using their difference in elevation angle. In the second part of this thesis, we use a long integration time and include extra information on the time model of a range cell signal : Doppler frequency variation. A collision target does not exhibit Doppler frequency variation, whereas fixed obstacle or ground clutter exhibits a known variation depending on the carrier velocity and the aspect angle. We take advantage of this variation first to separate a cable from a pylon, and then separate collision target from ground clutter. We finally tackle the problem of adaptively detecting a collision mobile spread target in ground clutter region. The proposed algorithms in this thesis have been successively tested on experimental data.

La collision entre l'ion hydroxyle (OH+) et l'atome d'hydrogène (H) joue un rôle majeur en physico-chimie de l'atmosphère et en astrophysique. Pour l'étude de ce système, nous avons générés la surface d'énergie potentielle tridimensionnelle (SEP-3D) globale doublet de la réaction H + OH+ --- H2O+ (X2B1)--- O + H2+. Les calculs électroniques ont été effectués au niveau MRCI avec la base aug-cc-pV5Z en incluant la correction des erreurs de superposition de base (BSSE). Cette SEP couvre la région moléculaire et les régions des longues portées pour les différents canaux : OH+ + H, O + H2+ et la réaction d'échange d'hydrogène. La qualité de la SEP a été validée après une comparaison des constantes spectroscopiques de H2O+ (X2B1) et des fragments diatomiques, des niveaux rovibroniques de H2O+ (X2B1), l'énergie de dissociation et de la barrière à linéarité pour H2O+ (X2B1) aux données expérimentales et théoriques existantes. Un bon accord est trouvé. Après avoir déterminé la SEP, nous avons utilisé les outils de la dynamique quantique indépendante du temps pour calculer les sections efficaces élastiques et inélastiques désexcitation de OH+ (v=0, j=1, 2, 3, 4, 5, 6 et 7) en collision avec l'atome d'hydrogène sur un large domaine d'énergie cinétique. Nous avons ainsi déterminé les taux désexcitation rotationnelle pour des températures allant de 10 à 200K. Nous avons également utilisé la surface quadruplet de Martinez et al. pour déduire ces taux désexcitation. Les résultats montrent que les sections efficaces inélastiques calculées sur la surface doublet sont en moyenne au moins deux à trois fois plus importantes que leurs correspondantes obtenues sur la surface quartet. Les potentiels à longue portée des deux surfaces étant identiques, ce résultat montre qu'un modèle basé sur la seule longue portée du potentiel ne pourrait pas rendre compte de la dynamique inélastique de ce système / The collision between the hydroxyl cation (OH+) and hydrogen atoms (H) plays a major role in physical chemistry of the atmosphere and astrophysics. To study this system, we generated the global three-dimensional potential energy surface (3D-PES) of the reaction H + OH+ ---- H2O+ (X2B1) ---- O + H2+. The electronic calculations were performed at the MRCI level with aug-cc-pV5Z basis including the basis set superposition error (BSSE) correction. This PES covers the molecular region and the long ranges close to the OH+ + H, O + H2+ and the hydrogen exchange channels. The quality of the PES is checked after comparison of the spectroscopic constants of H2O+ (X2B1) and of the diatomic fragments, the rovibronic levels, the dissociation energy, and the barrier to linearity of H2O+ (X2B1) to available experimental and theoretical data. A good agreement is found. Then, we used the tools of time-independent Quantum Dynamics to calculate the elastic and inelastic cross sections for the de-excitation of OH+ in collision with the hydrogen atom over a wide range of kinetic energy. We have thus determined the rotational de-excitation rate coefficients for temperatures ranging from 10 up to 200K. The results show that the inelastic cross sections on the doublet surface are on average at least two to three times larger than their cross section obtained on the previously computed cross sections using the quartet surface. Since, the long range parts of the doublet and the quartet PESs are identical, our work invalidates hence previous cross section determination. When only long range potentials are considered. Therefore, we recommend using fully the global 3D PES for scattering and reactive collision relevant for atmospheric and astrophysical studies

Este trabalho propõe um sistema de manipulação robótica para interação física segura com objetos ou humanos em ambientes não estruturados. A proposta considera a execução de tarefas de manipulação e a prevenção e tratamento de colisões utilizando apenas uma lei de controle, o controle de impedância. A inovação científica consiste em um sistema multifuncional implementado com uma única lei de controle em contraste com os sistemas já existem que utilizam chaveamento entre controladores para cada diferente funcionalidade do sistema, e que apresentam diversas desvantagens como instabilidade e oscilações, aumento da complexidade de programação, entre outras. Inicialmente é proposto um planejador de manipulação e regrasping baseado na combinação de trajetórias suaves e na adaptação dos parâmetros de um controle de impedância em tempo de execução. A mudança da impedância para cada etapa é obtida pela modificação dos parâmetros de inércia, rigidez e amortecimento do controlador. A estabilidade desta mudança dinâmica é possível pela utilização de trajetórias suaves obtidas com planejador Squeezed Screw modificado, cujas trajetórias geradas são livres de descontinuidades na posição e na velocidade. Adicionalmente, a prevenção de colisões é realizada com o auxílio de campos potenciais de forças de repulsão formados pela análise de dados de um sistema de visão também proposto. Estes mesmos dados são utilizados para a construção de um mapa de impedâncias ao redor do objeto cuja finalidade é suavizar efeitos de colisões indesejadas. Experimentos com um robô de arquitetura aberta e com um sistema de visão de baixo custo foram realizados na execução tarefa de manipulação de referência para se avaliar o desempenho da metodologia proposta em diferentes condições de operação encontradas em ambientes não estruturados, como por exemplo: erros de medida de posição, de calibração, ocorrência de colisões, etc. A tarefa de manipulação eleita foi a reorientação em 60° de um objeto circular no plano. Os resultados obtidos nos experimentos mostram a capacidade do controle de impedância associado a trajetórias suaves de realizar a tarefa eleita segundo avaliação utilizando como métricas de desempenho a porcentagem de reorientação, que apresentou uma média de 80% mesmo na presença de erros de medida do sensor de visão e erros de determinação da posição do objeto. / Recent applications in various robotics areas consider interaction between robots and objects or humans in non-structured environments. Under these conditions, in addition to the desire of robots to be able to perform their main tasks, handling, navigation, rehabilitation, etc, it is also desired to prevent and properly handle possible unwanted collisions, whether with objects, with other robots, animals or humans. There are several proposed methods for avoidance, handling and reaction for collisions, however, a widely used strategy is the controller switching between different robot states. There are several drawbacks within this strategy: instability and oscillation, increased programming complexity and consequent increased failure risk, need for different sensors and consequent increase in cost, among others. This work proposes a system applied to the robotic manipulation which is based on only one control law, the impedance control, whose expected capacity is, further performing manipulation tasks, avoidance and handling of potential undesired collisions. It is initially proposed a manipulation planner based the combination of smooth trajectories and the adjustment of parameters an impedance control at runtime. The change of impedance for each phase is achieved by modifying the parameters: mass, spring and damping controller. The stability of this dynamic change is possible by using smooth trajectories obtained with a modified Squeezed Screw trajectory planner, whose paths are discontinuities free in the position and speed. Additionally, collision avoidance is achieved through potential fields the repulsive forces of formed by analysis of data vision. The same data is used to construct an impedance map surrounding the object which objective is collision handling. Experiments with an open architecture robot and a low cost vision system are carried out in the execution of a benchmark manipulation task to evaluate the proposal performance under different operating conditions found in unstructured environments, for example, position measurement errors, calibration problems, occurrence of collisions, among others.

Previous research efforts aimed at understanding the relationship between automation reliability and reliance on the automation have mainly focused on a single dimension of reliability, the automations error rate. Efforts to understand the effects of additional dimensions, such as types of errors, have merely provided suggestions about the effects that automation false alarms and misses can have on human behavior). Furthermore, other dimensions of reliability, such as the distribution of errors in time, have been almost completely ignored. A multi-task simulation of an agricultural vehicle was used in this investigation. The simulator was composed of two main tasks, a collision avoidance task and a tracking task. The collision avoidance task was supported by an imperfect automated collision avoidance system and the tracking task was performed manually. The results of this investigation indicated that there are distinct patterns of reliance that develop as a function of error type, which are dependent on the state of the automation (alarms or non-alarms). The different distributions of errors across time had an effect on the estimates of reliability and subjective trust ratings. The recency of errors was negatively related to perceived reliability and trust. The results of the current investigation also suggest that older adults are able to adjust their behavior according to the characteristics of the automation, although it takes them longer to do so. Furthermore, it appears that older adults are willing to use automated systems, as long as they are reliable enough to reduce workload.